{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 项目：分析鸢尾花种类数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析目标"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "此数据分析报告的目的是基于鸢尾花的属性数据，分析两种鸢尾花萼片、花瓣的长度和宽度平均值，是否存在显著性差异，让我们可以对不同种类鸢尾花的属性特征进行推断。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 简介"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "原始数据`Iris.csv`包括两种鸢尾花，每种有 50 个样本，以及每个样本的一些属性，包括萼片的长度和宽度、花瓣的长度和宽度。\n",
    "\n",
    "`Iris.csv`每列的含义如下：\n",
    "- Id：样本的ID。\n",
    "- SepalLengthCm：萼片的长度（单位为厘米）。\n",
    "- SepalWidthCm：萼片的宽度（单位为厘米）。\n",
    "- PetalLengthCm：花瓣的长度（单位为厘米）。\n",
    "- PetalWidthCm：花瓣的宽度（单位为厘米）。\n",
    "- Species：鸢尾花种类。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读取数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "导入数据分析所需要的库，并通过Pandas的`read_csv`函数，将原始数据文件`Iris.csv`里的数据内容，解析为DataFrame并赋值给变量`original_data`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "original_data = pd.read_csv(\"Iris.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm      Species\n",
       "0   1            5.1           3.5            1.4           0.2  Iris-setosa\n",
       "1   2            4.9           3.0            1.4           0.2  Iris-setosa\n",
       "2   3            4.7           3.2            1.3           0.2  Iris-setosa\n",
       "3   4            4.6           3.1            1.5           0.2  Iris-setosa\n",
       "4   5            5.0           3.6            1.4           0.2  Iris-setosa"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "original_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 评估和清理数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在这一部分中，我们将对在上一部分建立的`original_data`DataFrame所包含的数据进行评估和清理。\n",
    "\n",
    "主要从两个方面进行：结构和内容，即整齐度和干净度。\n",
    "\n",
    "数据的结构性问题指不符合“每个变量为一列，每个观察值为一行，每种类型的观察单位为一个表格”这三个标准；数据的内容性问题包括存在丢失数据、重复数据、无效数据等。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为了区分开经过清理的数据和原始的数据，我们创建新的变量`cleaned_data`，让它为`original_data`复制出的副本。我们之后的清理步骤都将被运用在`cleaned_data`上。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cleaned_data = original_data.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据整齐度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>5.4</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.4</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>4.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm      Species\n",
       "0   1            5.1           3.5            1.4           0.2  Iris-setosa\n",
       "1   2            4.9           3.0            1.4           0.2  Iris-setosa\n",
       "2   3            4.7           3.2            1.3           0.2  Iris-setosa\n",
       "3   4            4.6           3.1            1.5           0.2  Iris-setosa\n",
       "4   5            5.0           3.6            1.4           0.2  Iris-setosa\n",
       "5   6            5.4           3.9            1.7           0.4  Iris-setosa\n",
       "6   7            4.6           3.4            1.4           0.3  Iris-setosa\n",
       "7   8            5.0           3.4            1.5           0.2  Iris-setosa\n",
       "8   9            4.4           2.9            1.4           0.2  Iris-setosa\n",
       "9  10            4.9           3.1            1.5           0.1  Iris-setosa"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从头部的10行数据来看，数据符合“每个变量为一列，每个观察值为一行，每种类型的观察单位为一个表格”，因此不存在结构性问题。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据干净度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来通过`info`，对数据内容进行大致了解。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 100 entries, 0 to 99\n",
      "Data columns (total 6 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Id             100 non-null    int64  \n",
      " 1   SepalLengthCm  100 non-null    float64\n",
      " 2   SepalWidthCm   100 non-null    float64\n",
      " 3   PetalLengthCm  100 non-null    float64\n",
      " 4   PetalWidthCm   100 non-null    float64\n",
      " 5   Species        100 non-null    object \n",
      "dtypes: float64(4), int64(1), object(1)\n",
      "memory usage: 4.8+ KB\n"
     ]
    }
   ],
   "source": [
    "cleaned_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从输出结果来看，`cleaned_data`数据共有100条观察值，不存在缺失值。\n",
    "\n",
    "`Id`表示样本ID，数据类型不应为数字，应为字符串，所以需要进行数据格式转换。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       2\n",
       "2       3\n",
       "3       4\n",
       "4       5\n",
       "     ... \n",
       "95     96\n",
       "96     97\n",
       "97     98\n",
       "98     99\n",
       "99    100\n",
       "Name: Id, Length: 100, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data[\"Id\"] = cleaned_data[\"Id\"].astype(\"str\")\n",
    "cleaned_data[\"Id\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 处理缺失数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从`info`方法的输出结果来看，`cleaned_data`不存在缺失值，因此不需要对缺失数据进行处理。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 处理重复数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根据数据变量的含义以及内容来看，`cleaned_data`里的`Id`是样本的唯一标识符，不应该存在重复，因此查看是否存在重复值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data[\"Id\"].duplicated().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "输出结果为0，说明不存在重复值。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 处理不一致数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "不一致数据可能存在于`Species`变量中，我们要查看是否存在多个不同值指代同一鸢尾花种类的情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Species\n",
       "Iris-setosa        50\n",
       "Iris-versicolor    50\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data[\"Species\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从以上输出结果来看，`Species`只有两种可能的值，`Iris-versicolor`和`Iris-setosa`，不存在不一致数据。\n",
    "\n",
    "我们可以把这列的类型转换为`Category`，好处是比字符串类型更节约内存空间，也能表明说值的类型有限。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         Iris-setosa\n",
       "1         Iris-setosa\n",
       "2         Iris-setosa\n",
       "3         Iris-setosa\n",
       "4         Iris-setosa\n",
       "           ...       \n",
       "95    Iris-versicolor\n",
       "96    Iris-versicolor\n",
       "97    Iris-versicolor\n",
       "98    Iris-versicolor\n",
       "99    Iris-versicolor\n",
       "Name: Species, Length: 100, dtype: category\n",
       "Categories (2, object): ['Iris-setosa', 'Iris-versicolor']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data[\"Species\"] = cleaned_data[\"Species\"].astype(\"category\")\n",
    "cleaned_data[\"Species\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 处理无效或错误数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以通过DataFrame的`describe`方法，对数值统计信息进行快速了解。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.471000</td>\n",
       "      <td>3.094000</td>\n",
       "      <td>2.862000</td>\n",
       "      <td>0.785000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.641698</td>\n",
       "      <td>0.476057</td>\n",
       "      <td>1.448565</td>\n",
       "      <td>0.566288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.300000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.400000</td>\n",
       "      <td>3.050000</td>\n",
       "      <td>2.450000</td>\n",
       "      <td>0.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.900000</td>\n",
       "      <td>3.400000</td>\n",
       "      <td>4.325000</td>\n",
       "      <td>1.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.000000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>1.800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm\n",
       "count     100.000000    100.000000     100.000000    100.000000\n",
       "mean        5.471000      3.094000       2.862000      0.785000\n",
       "std         0.641698      0.476057       1.448565      0.566288\n",
       "min         4.300000      2.000000       1.000000      0.100000\n",
       "25%         5.000000      2.800000       1.500000      0.200000\n",
       "50%         5.400000      3.050000       2.450000      0.800000\n",
       "75%         5.900000      3.400000       4.325000      1.300000\n",
       "max         7.000000      4.400000       5.100000      1.800000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cleaned_data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从以上统计信息来看，`cleaned_data`里不存在脱离现实意义的数值。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 整理数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对数据的整理，与分析方向紧密相关。此次数据分析目标是，基于鸢尾花的属性数据，分析两种鸢尾花萼片、花瓣的长度和宽度平均值，是否存在显著性差异。\n",
    "\n",
    "那么我们可以对数据基于`Species`列，先把各个鸢尾花种类样本数据筛选出来。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Id  SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm      Species\n",
       "0  1            5.1           3.5            1.4           0.2  Iris-setosa\n",
       "1  2            4.9           3.0            1.4           0.2  Iris-setosa\n",
       "2  3            4.7           3.2            1.3           0.2  Iris-setosa\n",
       "3  4            4.6           3.1            1.5           0.2  Iris-setosa\n",
       "4  5            5.0           3.6            1.4           0.2  Iris-setosa"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_setosa = cleaned_data.query('Species == \"Iris-setosa\"')\n",
    "iris_setosa.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(iris_setosa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>SepalLengthCm</th>\n",
       "      <th>SepalWidthCm</th>\n",
       "      <th>PetalLengthCm</th>\n",
       "      <th>PetalWidthCm</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>51</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>1.4</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>52</td>\n",
       "      <td>6.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>53</td>\n",
       "      <td>6.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>4.9</td>\n",
       "      <td>1.5</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>54</td>\n",
       "      <td>5.5</td>\n",
       "      <td>2.3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.3</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>55</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>Iris-versicolor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Id  SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm  \\\n",
       "50  51            7.0           3.2            4.7           1.4   \n",
       "51  52            6.4           3.2            4.5           1.5   \n",
       "52  53            6.9           3.1            4.9           1.5   \n",
       "53  54            5.5           2.3            4.0           1.3   \n",
       "54  55            6.5           2.8            4.6           1.5   \n",
       "\n",
       "            Species  \n",
       "50  Iris-versicolor  \n",
       "51  Iris-versicolor  \n",
       "52  Iris-versicolor  \n",
       "53  Iris-versicolor  \n",
       "54  Iris-versicolor  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris_versicolor = cleaned_data.query('Species == \"Iris-versicolor\"')\n",
    "iris_versicolor.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(iris_versicolor)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 探索数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在着手推断统计学分析之前，我们可以先借助数据可视化，探索`Setosa`和`Versicolor`这两种鸢尾花的变量特点。\n",
    "\n",
    "可视化探索可以帮我们对数据有一个更直观的理解，比如了解数据的分布、发现变量之间的关系，等等，从而为后续的进一步分析提供方向。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "针对数值，我们可以直接绘制成对图，利用其中的密度图查看不同变量的分布，以及利用散点图了解变量之间的关系。\n",
    "\n",
    "并且，由于此次分析目的是了解不同种类鸢尾花的属性特征是否存在差异，我们可以利用颜色对图表上不种类类的样本进行分类。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1143x1000 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(cleaned_data, hue=\"Species\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从以上可以看出，`Setosa`和`Versicolor`样本的花瓣长度以及花瓣宽度的分布存在明显数值上的不同，已经可以猜测假设检验的结果是，两种鸢尾花的花瓣长度与宽度有统计显著性差异。\n",
    "\n",
    "萼片的长度和宽度在分布上存在重叠，暂时无法仅通过图表下结论，需要进行假设检验，来推断总体的萼片长度和宽度之间是否有差异。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分析数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将利用假设检验，依次检验`Setosa`和`Versicolor`这两种鸢尾花在萼片、花瓣的长度和宽度平均值方面，是否存在统计显著性差异。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只有样本数据，不知道总体的标准差，加上两组样本数各为50，样本数量不大，因此进行t检验，而不是z检验。假设此数据集样本符合t检验的两个前提：样本为随机抽样，总体呈正态分布。\n",
    "\n",
    "我们先引入t检验所需要的模块。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import ttest_ind"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析萼片长度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setosa 和 Versicolor 萼片长度的分布如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(iris_setosa[\"SepalLengthCm\"],binwidth=0.1)\n",
    "sns.histplot(iris_versicolor[\"SepalLengthCm\"],binwidth=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立假设"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$H_0$：Setosa鸢尾花和Versicolor鸢尾花萼片长度的平均值不存在显著区别。\n",
    "\n",
    "$H_1$：Setosa鸢尾花和Versicolor鸢尾花萼片长度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确认检验是单尾还是双尾"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只检验平均值是否存在差异，不在乎哪个品种的萼片更长，所以是双尾检验。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确定显著水平"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将选择0.05作为显著水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算t值和p值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_stat, p_value = ttest_ind(iris_setosa[\"SepalLengthCm\"],iris_versicolor[\"SepalLengthCm\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t值：-10.52098626754911\n",
      "p值：8.985235037487079e-18\n"
     ]
    }
   ],
   "source": [
    "print(f\"t值：{t_stat}\")\n",
    "print(f\"p值：{p_value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于p值小于显著水平0.05，我们因此拒绝原假设，说明Setosa鸢尾花和Versicolor鸢尾花萼片长度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析萼片宽度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setosa 和 Versicolor 萼片长度的分布如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(iris_setosa['SepalWidthCm'], binwidth=0.1)\n",
    "sns.histplot(iris_versicolor['SepalWidthCm'], binwidth=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立假设"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$H_0$：Setosa鸢尾花和Versicolor鸢尾花萼片宽度的平均值不存在显著区别。\n",
    "\n",
    "$H_1$：Setosa鸢尾花和Versicolor鸢尾花萼片宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确认检验是单尾还是双尾"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只检验平均值是否存在差异，不在乎哪个品种的萼片更宽，所以是双尾检验。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确定显著水平"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将选择0.05作为显著水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算t值和p值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_stat, p_value = ttest_ind(iris_setosa[\"SepalWidthCm\"],iris_versicolor[\"SepalWidthCm\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t值：9.282772555558111\n",
      "p值：4.362239016010214e-15\n"
     ]
    }
   ],
   "source": [
    "print(f\"t值：{t_stat}\")\n",
    "print(f\"p值：{p_value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于p值小于显著水平0.05，我们因此拒绝原假设，说明Setosa鸢尾花和Versicolor鸢尾花萼片宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析花瓣长度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setosa 和 Versicolor 花瓣长度的分布如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(iris_setosa['PetalLengthCm'], binwidth=0.1)\n",
    "sns.histplot(iris_versicolor['PetalLengthCm'], binwidth=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立假设"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$H_0$：Setosa鸢尾花和Versicolor鸢尾花花瓣长度的平均值不存在显著区别。\n",
    "\n",
    "$H_1$：Setosa鸢尾花和Versicolor鸢尾花花瓣长度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确认检验是单尾还是双尾"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只检验平均值是否存在差异，不在乎哪个品种的花瓣更长，所以是双尾检验。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确定显著水平"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将选择0.05作为显著水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算t值和p值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_stat, p_value = ttest_ind(iris_setosa[\"PetalLengthCm\"],iris_versicolor[\"PetalLengthCm\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t值：-39.46866259397272\n",
      "p值：5.717463758170621e-62\n"
     ]
    }
   ],
   "source": [
    "print(f\"t值：{t_stat}\")\n",
    "print(f\"p值：{p_value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于p值小于显著水平0.05，我们因此拒绝原假设，说明Setosa鸢尾花和Versicolor鸢尾花萼片宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分析花瓣宽度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setosa 和 Versicolor 花瓣宽度的分布如下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(iris_setosa['PetalWidthCm'], binwidth=0.1)\n",
    "sns.histplot(iris_versicolor['PetalWidthCm'], binwidth=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立假设"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$H_0$：Setosa鸢尾花和Versicolor鸢尾花花瓣宽度的平均值不存在显著区别。\n",
    "\n",
    "$H_1$：Setosa鸢尾花和Versicolor鸢尾花花瓣宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确认检验是单尾还是双尾"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于我们只检验平均值是否存在差异，不在乎哪个品种的花瓣更宽，所以是双尾检验。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 确定显著水平"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们将选择0.05作为显著水平。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 计算t值和p值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_stat, p_value = ttest_ind(iris_setosa[\"PetalWidthCm\"],iris_versicolor[\"PetalWidthCm\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "t值：-34.01237858829048\n",
      "p值：4.589080615710866e-56\n"
     ]
    }
   ],
   "source": [
    "print(f\"t值：{t_stat}\")\n",
    "print(f\"p值：{p_value}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于p值小于显著水平0.05，我们因此拒绝原假设，说明Setosa鸢尾花和Versicolor鸢尾花花瓣宽度的平均值存在显著区别。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 结论"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过推论统计学的计算过程，我们发现，Setosa鸢尾花和Versicolor鸢尾花萼片、花瓣的长度和宽度平均值，均存在具有统计显著性的差异。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
